Advances in high-speed packet switching and fiber optic technology have opened the possibility of providing switching and transmission capacity from several 100 Mbits/second to several Gbits/second in a packet switched environment. However, the processing power and the ability to provide large amount of high speed buffers may not keep pace with the advances in transmission speeds. As a consequence, the dominant source of packet or cell loss in such networks would be due to buffer overflow. In low speed networks, flow and congestion control have been based on reactive mechanisms. These include the logical link controls, and end-to-end flow controls based on windows or credits. Such reactive or feedback controls essentially throttle the upstream node or the source, as the case may be, when the network experiences congestion. Such controls have been effective because the queueing delays in low speed networks have been much larger than the propagation delays. As a result, the sources were able to react to overloads before the state of the system changed significantly. In contrast, in high speed networks, where propagation delay dominates, reactive feedback controls tend to be too slow to be effective. The speed with which congestion sets in or dissipates is proportional to the speed of the link. Because the state of individual nodes can change rapidly, feedback information will be out of date if the time to propagate the information is longer than the node time constants.
A common flow or congestion control scheme in low speed networks has been the use of end-to-end flow control based on windows. For example, for each connection or virtual circuit (VC), the maximum number of unacknowledged packets is limited to a window of W packets. In order to ensure very low packet loss due to too many VCs becoming active at the same time, one has to allocate a window's worth of buffer for every VC at every node on the VC's path. In high speed wide area networks, the number of VCs can be very large, and the required window to obtain high throughput is also large because of the large bandwidth delay product, and this can translate to an unrealistic number of buffers in the network. Further, a combination of large number of VCs, each with a large window, can lead to severe congestion when too many VCs become active at the same time. An alternative is to use an adaptive end-to-end control, where the window size is modulated based on the state of the nodes on the VC's path. However, the effectiveness of such a scheme diminishes as the bandwidth delay product increases.
Unlike reactive controls that allow congestion to develop in the first place and then react to it, congestion avoidance strategies try to avoid congestion in the first place, through conservative admission policies. Such admission controls result in admission delays which are of the order of queueing delays (which is low at high speeds) and can be easily tolerated by many applications, if a low cell loss can be guaranteed. Cell loss on the other hand leads to retransmission, and the resulting delay can be of the order of propagation delay. Such congestion avoidance strategies are generally based on controlling the rate at which cells are admitted into the network. In most static rate control schemes, an estimate of the average available bandwidth (for the class of traffic being controlled) is made. For example, if the average bandwidth usage by higher priority services, such as voice and video, is .lambda..sub.X (this is known from the call admission control), and if the link bandwidth is .lambda..sub.L, then the average available excess capacity .lambda..sub.C =.lambda..sub.L -.lambda..sub.X. The static rate controls ensure that the combined arrival rate of the rate controlled low priority class is limited to some value r.lambda..sub.C (0&lt;r&lt;1). The problem with this approach is that in the short run, the excess capacity can momentarily reduce to zero and can remain at that level for a time that is much larger than the amount of buffers available at the congested node. This would lead to large cell losses, especially if the factor r is large. For the cell loss rate to be low, r has to be much smaller than 1, leading to under-utilization of the link. Several end-to-end schemes have been proposed which attempt to detect congestion and regulate the sources accordingly. End-to-end adaptive schemes however can be effective only when the round trip propagation delays are small compared to the queue time constants. It can be shown that the adaptive end-to-end rate control scheme can at best perform only as well as an optimum static rate control scheme. The disadvantage of the static rate control scheme is that if low cell loss is required, then the scheme results in low utilization. Any attempt to increase the utilization results in an increase in cell loss. However, end-to-end control schemes may be effective in high speed networks with small round trip delays such MANs and LANs.
Feedback flow control can be classified as static or adaptive, and it can be based on an end-to-end window mechanism or can be rate based. In the static window mechanism, the number of unacknowledged messages in the network is limited by the window size. In adaptive window control schemes, the congested nodes send congestion signals to the source and the source in turn responds by modifying its window size. In one known system, the optimum end-to-end window is measured by the round trip response time of packets and the window is adjusted dynamically. In another known system, a feed forward rate control at the access node operates under an end-to-end window control that stabilizes the open loop rate control. In the event of congestion, the end-to-end window control can be reduced by the congested nodes which in turn quenches the source. The source responds by reducing its rate. In another system, a packet pair probing technique in conjunction with round robin scheduling by virtual circuits at each node is used to determine the level of congestion in the network, and an appropriate control algorithm is used to control the source rate.
In another study, the performance of a threshold based feedback control policy in a high-speed network with significant propagation delay has been investigated. The principal difficulty with high-speed wire area networks is the long round trip delay, which makes end-to-end controls ineffective. A knowledge of the state of the nodes on the VC's path cannot be exploited because of the large round trip propagation delays. Since the timeliness of the state information is determined by the propagation delay and the rate at which the state of the queues are changing, myopic controls are more meaningful. For example, feedback controls between adjacent nodes that are not separated by large delays will be more effective than feedback between edge nodes.